Molecular Autonomous Pathfinder Using Deep Reinforcement Learning

Nomura, Ken-ichi; Mishra, Ankit; Sang, Tian; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

doi:10.1021/acs.jpclett.4c00438

Title: Molecular Autonomous Pathfinder Using Deep Reinforcement Learning

Journal Article · 08 May 2024 · Journal of Physical Chemistry Letters

DOI: https://doi.org/10.1021/acs.jpclett.4c00438 · OSTI ID:2349144

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^[1]; Sang, Tian ^[1]; Kalia, Rajiv K. ^[1];

^[1];

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Collaboratory for Advanced Computing and Simulations, University of Southern California, Los Angeles, California 90089, United States

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Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0023146

OSTI ID:: 2349144

Alternate ID(s):: OSTI ID: 2472325

Journal Information:: Journal of Physical Chemistry Letters, Journal Name: Journal of Physical Chemistry Letters Journal Issue: 19 Vol. 15; ISSN 1948-7185

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

References (47)

Fast Diffusion in Semiconductors Gosele, U. M. Annual Review of Materials Science, Vol. 18, Issue 1 https://doi.org/10.1146/annurev.ms.18.080188.001353	journal	August 1988
Static and kinematic shakedown theorems in diffusion-induced plasticity Peigney, Michael Journal of Theoretical and Applied Mechanics, Vol. 58, Issue 2 https://doi.org/10.15632/jtam-pl/118453	journal	April 2020
Mastering the game of Go with deep neural networks and tree search Silver, David; Huang, Aja; Maddison, Chris J. Nature, Vol. 529, Issue 7587 https://doi.org/10.1038/nature16961	journal	January 2016
Roman iron and steel: A review Lang, Janet Materials and Manufacturing Processes, Vol. 32, Issue 7-8 https://doi.org/10.1080/10426914.2017.1279326	journal	January 2017
Revealing the role of the cathode–electrolyte interface on solid-state batteries Zahiri, Beniamin; Patra, Arghya; Kiggins, Chadd Nature Materials, Vol. 20, Issue 10 https://doi.org/10.1038/s41563-021-01016-0	journal	May 2021
Human-level control through deep reinforcement learning Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David Nature, Vol. 518, Issue 7540 https://doi.org/10.1038/nature14236	journal	February 2015
The Diffusion of Helium and of Hydrogen Through Pyrex Chemically Resistant Glass Taylor, Nelson W.; Rast, William The Journal of Chemical Physics, Vol. 6, Issue 10 https://doi.org/10.1063/1.1750133	journal	October 1938
The ReaxFF reactive force-field: development, applications and future directions Senftle, Thomas P.; Hong, Sungwook; Islam, Md Mahbubul npj Computational Materials, Vol. 2, Issue 1 https://doi.org/10.1038/npjcompumats.2015.11	journal	March 2016
Diffusion of water in silica glass Doremus, Robert H. Journal of Materials Research, Vol. 10, Issue 9 https://doi.org/10.1557/JMR.1995.2379	journal	September 1995
Distributed Prioritized Experience Replay Horgan, Dan; Quan, John; Budden, David arXiv https://doi.org/10.48550/arXiv.1803.00933	preprint	January 2018
Autonomous reinforcement learning agent for chemical vapor deposition synthesis of quantum materials Rajak, Pankaj; Krishnamoorthy, Aravind; Mishra, Ankit npj Computational Materials, Vol. 7, Issue 1 https://doi.org/10.1038/s41524-021-00535-3	journal	July 2021
High-entropy alloys George, Easo P.; Raabe, Dierk; Ritchie, Robert O. Nature Reviews Materials, Vol. 4, Issue 8 https://doi.org/10.1038/s41578-019-0121-4	journal	June 2019
On liquid diffusion Fick, Adolph Journal of Membrane Science, Vol. 100, Issue 1 https://doi.org/10.1016/0376-7388(94)00230-V	journal	March 1995
ReaxFF: A Reactive Force Field for Hydrocarbons van Duin, Adri C. T.; Dasgupta, Siddharth; Lorant, Francois The Journal of Physical Chemistry A, Vol. 105, Issue 41 https://doi.org/10.1021/jp004368u	journal	October 2001
Diffusion of water in silica glass in the absence of stresses Wiederhorn, Sheldon M.; Rizzi, Gabriele; Wagner, Susanne Journal of the American Ceramic Society, Vol. 100, Issue 9 https://doi.org/10.1111/jace.14937	journal	May 2017
REINVENT 2.0: An AI Tool for De Novo Drug Design Blaschke, Thomas; Arús-Pous, Josep; Chen, Hongming Journal of Chemical Information and Modeling, Vol. 60, Issue 12 https://doi.org/10.1021/acs.jcim.0c00915	journal	October 2020
Aqueous alteration of silicate glass: state of knowledge and perspectives Gin, Stéphane; Delaye, Jean-Marc; Angeli, Frédéric npj Materials Degradation, Vol. 5, Issue 1 https://doi.org/10.1038/s41529-021-00190-5	journal	August 2021
Anton 3 Shaw, David E.; Adams, Peter J.; Azaria, Asaph Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis https://doi.org/10.1145/3458817.3487397	conference	November 2021
Deep reinforcement learning of transition states Zhang, Jun; Lei, Yao-Kun; Zhang, Zhen Physical Chemistry Chemical Physics, Vol. 23, Issue 11 https://doi.org/10.1039/D0CP06184K	journal	January 2021
Nanoscale mapping of ion diffusion in a lithium-ion battery cathode Balke, N.; Jesse, S.; Morozovska, A. N. Nature Nanotechnology, Vol. 5, Issue 10 https://doi.org/10.1038/nnano.2010.174	journal	August 2010
Water Interactions with Nanoporous Silica: Comparison of ReaxFF and ab Initio based Molecular Dynamics Simulations Rimsza, J. M.; Yeon, Jejoon; van Duin, A. C. T. The Journal of Physical Chemistry C, Vol. 120, Issue 43 https://doi.org/10.1021/acs.jpcc.6b07939	journal	October 2016
Lithium Diffusion Mechanism through Solid–Electrolyte Interphase in Rechargeable Lithium Batteries Ramasubramanian, Ajaykrishna; Yurkiv, Vitaliy; Foroozan, Tara The Journal of Physical Chemistry C, Vol. 123, Issue 16 https://doi.org/10.1021/acs.jpcc.9b00436	journal	March 2019
Corrosion defect assessment on pipes using limit analysis and notch fracture mechanics Hadj Meliani, M.; Matvienko, Y. G.; Pluvinage, G. Engineering Failure Analysis, Vol. 18, Issue 1 https://doi.org/10.1016/j.engfailanal.2010.09.006	journal	January 2011
Extending the Time Scale in Atomistic Simulation of Materials Voter, Arthur F.; Montalenti, Francesco; Germann, Timothy C. Annual Review of Materials Research, Vol. 32, Issue 1 https://doi.org/10.1146/annurev.matsci.32.112601.141541	journal	August 2002
Mastering the game of Go without human knowledge Silver, David; Schrittwieser, Julian; Simonyan, Karen Nature, Vol. 550, Issue 7676 https://doi.org/10.1038/nature24270	journal	October 2017
A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K. Computer Physics Communications, Vol. 219 https://doi.org/10.1016/j.cpc.2017.05.028	journal	October 2017
Diffusion of Water into Silica Glass at Low Temperature Wakabayashi, Hajimu; Tomozawa, Minoru Journal of the American Ceramic Society, Vol. 72, Issue 10 https://doi.org/10.1111/j.1151-2916.1989.tb05990.x	journal	October 1989
Accelerated Molecular Dynamics Methods: Introduction and Recent Developments Perez, Danny; Uberuaga, Blas P.; Shim, Yunsic Annual Reports in Computational Chemistry, Vol. 5, p. 79-98 https://doi.org/10.1016/S1574-1400(09)00504-0	book	January 2009
Molecular dynamics simulation of atomic hydrogen diffusion in strained amorphous silica* Zhang, Fu-Jie; Zhou, Bao-Hua; Liu, Xiao Chinese Physics B, Vol. 29, Issue 2 https://doi.org/10.1088/1674-1056/ab5fc5	journal	February 2020
Tunable chemical complexity to control atomic diffusion in alloys Osetsky, Yuri; Barashev, Alexander V.; Béland, Laurent K. npj Computational Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41524-020-0306-9	journal	April 2020
Point defects and dopant diffusion in silicon Fahey, P. M.; Griffin, P. B.; Plummer, J. D. Reviews of Modern Physics, Vol. 61, Issue 2 https://doi.org/10.1103/RevModPhys.61.289	journal	April 1989
Magnetic control of tokamak plasmas through deep reinforcement learning Degrave, Jonas; Felici, Federico; Buchli, Jonas Nature, Vol. 602, Issue 7897 https://doi.org/10.1038/s41586-021-04301-9	journal	February 2022
Addressing Action Oscillations through Learning Policy Inertia Chen, Chen; Tang, Hongyao; Hao, Jianye Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35, Issue 8 https://doi.org/10.1609/aaai.v35i8.16864	journal	May 2021
Tailoring atomic diffusion for in situ fabrication of different heterostructures Zhang, Hui; Xu, Tao; Yu, Kaihao Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-25194-2	journal	August 2021
Molecular de-novo design through deep reinforcement learning Olivecrona, Marcus; Blaschke, Thomas; Engkvist, Ola Journal of Cheminformatics, Vol. 9, Issue 1 https://doi.org/10.1186/s13321-017-0235-x	journal	September 2017
Sluggish diffusion in Co–Cr–Fe–Mn–Ni high-entropy alloys Tsai, K. -Y.; Tsai, M. -H.; Yeh, J. -W. Acta Materialia, Vol. 61, Issue 13 https://doi.org/10.1016/j.actamat.2013.04.058	journal	August 2013
Exponential multiplicity of inherent structures Stillinger, Frank H. Physical Review E, Vol. 59, Issue 1 https://doi.org/10.1103/PhysRevE.59.48	journal	January 1999
The future of electronics based on memristive systems Zidan, Mohammed A.; Strachan, John Paul; Lu, Wei D. Nature Electronics, Vol. 1, Issue 1 https://doi.org/10.1038/s41928-017-0006-8	journal	January 2018
Water diffusion in silica glass through pathways formed by hydroxyls Kuroda, Minami; Tachibana, Shogo; Sakamoto, Naoya American Mineralogist, Vol. 103, Issue 3 https://doi.org/10.2138/am-2018-6208	journal	March 2018
Q-learning Watkins, Christopher J. C. H.; Dayan, Peter Machine Learning, Vol. 8, Issue 3-4 https://doi.org/10.1007/BF00992698	journal	May 1992
Interaction potential for SiO 2 : A molecular-dynamics study of structural correlations Vashishta, P.; Kalia, Rajiv K.; Rino, José P. Physical Review B, Vol. 41, Issue 17 https://doi.org/10.1103/PhysRevB.41.12197	journal	June 1990
Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials Rajak, Pankaj; Wang, Beibei; Nomura, Ken-ichi npj Computational Materials, Vol. 7, Issue 1 https://doi.org/10.1038/s41524-021-00572-y	journal	July 2021
RXMD: A scalable reactive molecular dynamics simulator for optimized time-to-solution Nomura, Ken-ichi; Kalia, Rajiv K.; Nakano, Aiichiro SoftwareX, Vol. 11 https://doi.org/10.1016/j.softx.2019.100389	journal	January 2020
Fast diffusion path for water in silica glass Kuroda, Minami; Tachibana, Shogo; Sakamoto, Naoya American Mineralogist, Vol. 104, Issue 3 https://doi.org/10.2138/am-2019-6802	journal	March 2019
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing Wang, Zhongrui; Joshi, Saumil; Savel’ev, Sergey E. Nature Materials, Vol. 16, Issue 1 https://doi.org/10.1038/nmat4756	journal	September 2016
Rainbow: Combining Improvements in Deep Reinforcement Learning Hessel, Matteo; Modayil, Joseph; van Hasselt, Hado arXiv https://doi.org/10.48550/arXiv.1710.02298	preprint	January 2017
A solar wind-derived water reservoir on the Moon hosted by impact glass beads He, Huicun; Ji, Jianglong; Zhang, Yue Nature Geoscience, Vol. 16, Issue 4 https://doi.org/10.1038/s41561-023-01159-6	journal	March 2023

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